Abdominal aortic aneurysms (AAA) are common and can be life-threatening if they progress to rupture. They have been reported in 5% of older men and account for over 15,000 deaths per year. Basic vessel dimensions are currently the primary imaging measurement used clinically to risk-stratify patients. But there is more to the story than dimensions. Wall stress estimated with computational modeling may better predict growth and rupture than diameters. Growth is often not continuous, and instead marked by periods of rapid growth followed by quiescence. Small series report that unrelated surgical procedures can precipitate AAA rupture. These findings suggest that episodic and heterogeneous inflammatory processes in concert with adverse hemodynamics are important for the progression of AAA disease. The complexity of aortic disease is more fully revealed with new functional imaging techniques than with conventional anatomic analysis alone. While AAA has been extensively studied, the mechanisms of disease progression have not been fully elucidated. If better understood, the management of patients with small AAAs (< 5.5cm) could be significantly improved. Many of these aneurysms can be followed safely with a long screening interval of 2-3 years, but some may progress to rupture. Identifying this subset would greatly streamline the surveillance imaging of the millions of patients with AAA. On the other hand, the majority of AAAs never rupture, and identifying low risk patients could help better manage resources and subject only those patients at truly elevated risk to intervention. Aortic wall inflammation can be evaluated with the MRI contrast agent ferumoxytol, which has macrophage- selective properties on delayed imaging. MRI also offers a unique and comprehensive assessment of aortic hemodynamics. Blood flow imaging with time-resolved, 3D phase-contrast MRI (4D Flow) allows quantification of key secondary vascular parameters including turbulence and wall shear stress (WSS). Cine Displacement Encoding with Stimulated Echos (DENSE) can quantify regional stretch differences experienced by the vessel wall. Computational modeling based on MRI volumetric data can be used to calculate wall stress. The goal of our study is to uncover important inflammatory changes and adverse hemodynamics that are not addressed with current imaging, and use them to predict disease progression. We seek to meaningfully advance the assessment of risk in patients who do not meet current intervention thresholds and improve outcomes by refining surveillance imaging regimens and decisions regarding early intervention for AAAs.